The present invention relates to a measurement device and a data compressing method and, more particularly, to a wearable electrocardiogram measurement device and a method for compressing an electrocardiogram.
The heart is the most important and the most complicated organ among the human organs. With the development of technology, the operation and beating of the heart can be observed through instruments to judge whether abnormal heart conditions occur. An electrocardiogram (ECG) obtained by measuring the heart beating is one of the major judgement bases. To accurately capture the heart activity status, a 12-lead system (namely, 12-lead ECG) utilizes 12 leads on the front side and the horizontal plane to record the electrophysical activity of the heart from 12 different directions, obtaining 12 electrocardiogram data. Thus, a doctor can observe the operating pattern of the cardiac electrical pulses from 12 different angles to judge the heart activity status or to judge the causes of heart disease.
However, the electrocardiograms requires a long period of time of observation and recording plus measurement of the heart beating conditions from 12 different directions, the overall data is huge and occupies a considerable space of a hard disc. It is, thus, an important issue in preventing data distortion after compressing and decompressing while providing a better amount of compression. The value of the percentage root mean square difference (PRD) is the index of distortion and is preferably between 2% and 7%.
FIG. 3 is a diagrammatic block diagram illustrating a conventional method for compressing electrocardiogram data. A PRD value (the target value) is preset before the measurement. After the electrocardiogram data have undergone bandwidth decomposition, quantization, error control, and encoding, since the PRD value after decompression must fulfill the preset value, decoding analysis, inverse quantization, and inverse bandwidth decomposition must be conducted to compare the compressed data with the original data for judging whether the PRD is within 5% fluctuation range of the target value. After compression, since decoding analysis, inverse quantization, and inverse bandwidth decomposition must be carried out to permit comparison of the PRD value, the data compressing takes a long time and, thus, increases the burden to the processor. Furthermore, since obtaining the electrocardiogram data requires a considerable time for continuously observing the heart activity status, the patient must stay in the hospital for a long period of time, which is extremely inconvenient.
Thus, a need exists for a method for obtaining the electrocardiogram data without affecting the living of the patient. Furthermore, the PRD comparison can be proceeded while carrying out bandwidth decomposition, quantization, error control, and encoding. Thus, about half of the data compressing time can be saved to reduce the burden to the instrument.